Heretofore original documents carrying continuous intensity greyscale images were scanned into memory and digitized into a pixel matrix of discrete greyscale levels. Low contrast background noise on the original documents such as smudges of foreign substances, fiber grain, watermarks, off-color paper etc., became pixels of low intensity greyscale levels. Data compression of these digital images was impaired by the numerous low magnitude transitions in greyscale level within the background region which typically accounts for over 90% of the total document area. Later when the memory image was returned to hard copy by a printer, these low intensity greyscale pixels were faithfully reproduced on the hard copy. This background noise was randomly distributed in the non-stroke region, around and between the strokes (foreground signal) forming the symbols (text) of the image. The background noise distracted the reader and diverted the reader's full attention from the printed symbols. Reading the text contained in the original document and the reproduced hard copy was wearisome to the reader.
Ser. No. 08/112,133, filed Aug. 26, 1993 now abandoned to Roger D. Melen and Hadar Avi-Itzhak, and assigned to the present assignee, teaches the classification of an unknown input symbol with a library of known templates. The background pixels of the input symbol is clamped to zero to match the corresponding background pixels of the templates. The resulting higher match between the symbol and the template produces a higher correlation coefficient.